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SQL Optimizer

🔵 Stable🕐 updated 2026-06-28 🔷 SkillSpec L3 pm-dataeng

Diagnose a slow SQL query and produce a concrete optimization plan. Use when asked to optimize SQL, speed up a slow query, reduce a query's cost/scan, fix a timeout, or review a query plan. Produces an analysis — the likely bottleneck, what the plan is doing wrong (full scans, bad joins, spills), the specific rewrite and index/partition changes, and the expected impact, with the optimized query.

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What to give it

The query — (and the engine — Postgres, BigQuery, Snowflake, MySQL… optimizations differ).
The symptom — slow, expensive (bytes scanned), timing out, or just under review.
Context if available — `EXPLAIN`/query plan, table sizes/row counts, existing indexes, partitioning/clustering.

✅ The bar it holds itself to

Every skill in this library self-verifies — these are this skill's own quality checks, straight from its definition.

Names the single primary bottleneck, not a scattershot list
Predicates are checked for sargability (no functions on indexed columns, no leading `%`)
Index/partition recommendations are specific (exact columns), not "add an index"
For columnar/cloud engines, addresses bytes scanned & pruning, not just row counts
Provides the rewritten query and a way to verify the improvement

⚠️ What it refuses to do

Do not say "add indexes" generically — name the columns and explain which predicate/join they serve
Do not ignore the engine — Postgres index tuning and BigQuery partition pruning are different games
Do not optimize a query that should be a model — repeated heavy logic belongs in a materialized/dbt model
Do not wrap indexed columns in functions in the WHERE clause — it kills index usage (non-sargable)
Do not recommend changes without an expected impact or a way to measure it

Install

npx pm-claude-skills add --agent claude   # or codex · cursor · gemini · hermes
# or one-line MCP (every skill, any client):
claude mcp add pm-skills -- npx -y pm-claude-skills-mcp

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💬 Discussion

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